35.6: Critical Values for Grubb's Test

The following table provides critical values for \(G(\alpha, n)\), where \(\alpha\) is the probability of incorrectly rejecting the suspected outlier and n is the number of samples in the data set. There are several versions of Grubb’s Test, each of which calculates a value for G_ij where i is the number of suspected outliers on one end of the data set and j is the number of suspected outliers on the opposite end of the data set. The critical values for G given here are for a single outlier, G₁₀, where

\[G_\text{exp} = G_{10} = \frac {|X_{out} - \overline{X}|} {s} \nonumber \]

The suspected outlier is rejected if G_exp is greater than \(G(\alpha, n)\).

Table \(\PageIndex{1}\): Critical Values for the Grubb's Test

\(\frac {\alpha \ce{->}} {n \ce{ v }}\)	0.05	0.01
3	1.155	1.155
4	1.481	1.496
5	1.715	1.764
6	1.887	1.973
7	2.020	2.139
8	2.126	2.274
9	2.215	2.387
10	2.290	2.482
11	2.355	2.564
12	2.412	2.636
13	2.462	2.699
14	2.507	2.755
15	2.549	2.755

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